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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

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Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant

Lizelle Correia1, Ramiro Magno2, Joana M Xavier2

  • 1Faculty of Medicine and Biomedical Sciences (FMCB), Universidade do Algarve, Faro, Portugal.

NPJ Breast Cancer
|June 8, 2022
PubMed

Insights

Common PIK3CA mutations in breast cancer show allelic expression imbalance. This imbalance, driven by regulatory variants, predicts poor prognosis and may indicate limited benefit from PI3K inhibitors.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations are prevalent in breast cancer, especially in estrogen receptor-positive (ER+) subtypes.
  • Despite high mutation frequency, PI3K inhibitors have shown limited clinical success in breast cancer patients.
  • Understanding the expression patterns of mutant PIK3CA alleles is crucial for optimizing targeted therapies.

Purpose of the Study:

  • To investigate the allelic expression imbalance of PIK3CA mutations in breast cancer.
  • To identify the mechanisms driving PIK3CA allelic expression, such as cis-regulatory variants.
  • To correlate PIK3CA allelic expression patterns with clinical outcomes and response to PI3K inhibitors.

Main Methods:

  • Analysis of PIK3CA allelic expression in large breast cancer cohorts (METABRIC and TCGA).
  • Identification of regulatory variants in cis that influence PIK3CA allele-specific expression.
  • Statistical correlation of allelic expression imbalance with patient prognosis and tumor subtypes (ER, PR, HER2 status).

Main Results:

  • Frequent allelic expression imbalance of PIK3CA was observed in both METABRIC (70.2%) and TCGA (60.1%) datasets.
  • A significant proportion of tumors exhibited imbalance due to cis-regulatory variants (27.7% and 11.8%).
  • Preferential expression of the mutant PIK3CA allele, driven by cis-regulation, was associated with poor prognosis in METABRIC cohort (P=0.031).
  • ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets.

Conclusions:

  • PIK3CA allelic expression imbalance is a significant factor in breast cancer prognosis.
  • Identifying patients with PIK3CA allelic imbalance can help predict poorer outcomes.
  • Patients with low mutant PIK3CA allele expression may not benefit from PI3K inhibitors, suggesting a role in treatment selection.
  • Differential regulation of PIK3CA plays a critical role in breast cancer development and progression.

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